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VMware vFabric SQLFire is a memory-optimized distributed SQL database delivering dynamic scalability and high performance for data-intensive modern applications. SQLFire’s memory-optimized architecture minimizes time spent waiting for disk access, the main performance bottleneck in traditional databases. SQLFire achieves dramatic scaling by pooling memory, CPU and network bandwidth across a cluster of machines and can manage data across geographies. SQLFire provides developers with the well-known SQL interface and tools.

Developing Applications with SQLFire explains the main concepts of programming Java and ADO.NET applications with SQLFire APIs and the SQLFire implementation of SQL. It describes how to embed a SQLFire instance in a Java application and how to connect as a client. This guide also describes transactional and non-transactional behavior, and explains how to create data-aware stored procedures.

SQLFire RESOURCES

Tutorial: Integrating SQLFire with tc Server and Spring Data

This article describes basic instructions of SQLFire usage in a simple Java and Spring-based application deployed in vFabric tc Server. The sample application used is a Spring-ified version of Sun's J2EE PetStore application.

Banking Case Study: Scaling with Low Latency using NewSQL

In this presentation, Jags Ramnaryan, Chief Architect for GemFire products at VMWare walks through how a bank used a horizontally scalable, memory oriented SQL database (VMWare SQLFire), did minimal changes to its application, injected the Database between the app and its original database and achieved elastic (on-demand) scaling with very low latencies.

Introducing SQLFire: a memory-optimized, high performance SQL database

Fast meets scalable in VMware’s new distributed SQL database. VMware vFabric™ SQLFire is memory-optimized for maximum speed out of the box and gives you the scale you need in a substantially simpler way. SQLFire is designed for horizontal scalability, so if you need more capacity you simply add more nodes (or more virtual machines) and SQLFire will automatically rebalance data across all members for maximum performance. Watch this webcast to learn how SQLFire offers some of the best features usually seen only in NoSQL databases, all while providing a real SQL interface.

HIGHLIGHTS FROM THE SQLFire BLOG

Java Stored Procedure Performance: Myths vs. Facts

“Java Stored Procedures will never be as fast as SQL Stored Procedures” is a common refrain from database administrators based on their experience with stored procedures in “normal” relational databases.   However, SQLFire provides significant advantages for performance of stored procedures. SQL statements are byte compiled into Java structures and Java Stored Procedures run in the same memory and processing space that database operations are performed. Learn more in this blog. 

How to offload data from an existing data store and load it into SQLFire

A common requirement for using SQLFire is offloading data from an existing data store and loading it into SQLFire. This example shows how you can load data into a SQLFire distributed system using Spring Batch from a CSV file and then how to present the data from a simple Spring MVC application.

Using SQLFire as a read-only cache for MySQL

Putting a read-only cache atop an RDBMS helps by offloading some reads to another server.  A database that is constantly getting reads and writes for a lot of different users (high concurrency) leads to disk thrashing which leads to extremely bad performance. Serving a portion of reads in-memory cuts down on this thrash, making your write throughput go up on the underlying database. In addition, an in-memory architecture like SQLFire handles high concurrency extremely well since it doesn't suffer from thrashing problems the way disk-based databases do.

SQLFire and Grails

Chris Harris has written a series of blog posts showing how to use SQLFire from within Grails. In the process he introduces a couple of very interesting features of SQLFire , specifically how your app should take advantage of SQLFire's elasticity and the possibility of using SQLFire as a cache.

Persistence Content on InfoQ


Latest featured content about Persistence

Jags Ramnarayan on In-Memory Data Grids

Sections
Architecture & Design
Topics
Persistence,
Polyglot Persistence,
Architecture,
In-Memory Persistence,
Data Storage,
Database

In-memory data grids (IMDG) are gaining lot of attention recently because of their support for dynamic scalability and high performance for data intensive applications. InfoQ spoke with Jags Ramnarayan, Chief Architect for GemFire products at VMWare, about the architecture of in-memory data grids, their advantages compared to the traditional databases, and emerging trends in this space.

News about Persistence

VMware's vFabric Suite Gains Automated Deployment and PostgreSQL Support

Sections
Operations & Infrastructure,
Development
Topics
Java,
Virtualization,
Cloud Foundry,
VMWare vFabric SQLFire,
Languages,
Infrastructure,
VMWare,
IaaS,
Relational Databases,
Persistence,
vFabric,
Companies,
Programming,
Cloud Computing,
Database

VMware has today announced VMware vFabric Suite 5.1, adding automated deployment, enterprise open source support, and PostgreSQL capabilities, as well as an expansion to the SQLFire in-memory database.

Hibernate 4.1 Released With Improved Auditing Support

Sections
Operations & Infrastructure,
Architecture & Design,
Development
Topics
JBoss,
RedHat,
Application Servers,
Java,
Companies,
Languages,
Persistence,
Data Access,
Database,
Envers,
Programming,
Security,
Hibernate

JBoss relases Hibernate 4.1 with improvements to the Envers module that allow for finding the database revision responsible for a change in a specific audited property.

VMware Releases SQLFire 1.0

Sections
Operations & Infrastructure,
Architecture & Design
Topics
Java,
SpringSource,
SQL,
Caching,
Relational Databases,
Languages,
VMWare,
Clustering & Caching,
Persistence,
Data Access,
Programming,
Infrastructure,
Database,
Performance & Scalability,
Data Partitioning,
Database Replication,
GemFire,
vFabric,
Companies

VMware releases SQLFire 1.0 a distributed SQL database geared towards high availability and horizontal scalability which offers table replication, table partitioning and parallel execution of queries.

Articles about Persistence

Revving Up Your Hibernate Engine

Sections
Architecture & Design,
Development
Topics
Java,
Languages,
Persistence,
Programming,
Database,
Hibernate,
Performance & Scalability

This article explores tuning techniques for Hibernate-based applications, focusing on tuning topics that are effective but poorly documented, such as inheritance mapping, second level cache and enhanced sequence identifier generators. It also provides some background database information which is essential for tuning Hibernate.

Scaling Clojure Web Apps with Google AppEngine

Sections
Operations & Infrastructure,
Architecture & Design,
Development
Topics
Ruby,
Java,
Dynamic Languages,
Domain Specific Languages,
Google AppEngine,
Clojure,
JVM Languages,
LISP,
Languages,
Data Access,
Persistence,
PaaS,
Google,
Database,
Architecture,
Programming,
Cloud Computing,
Companies,
Performance & Scalability

InfoQ takes a look at how a combo of Clojure and Google AppEngine (GAE) powers a new online project management tool, how Clojure integrates with GAE's key/value store, and the power of LISP.

Presentations about Persistence

Basic Application Development with Spring Roo and SQLFire

Sections
Operations & Infrastructure,
Development
Topics
SpringOne 2GX 2011,
SpringOne,
Spring,
Conferences,
Java,
Dependency Injection,
SpringSource,
Languages,
Persistence,
Design Pattern,
VMWare,
Data Access,
Programming,
Database,
Design,
Patterns,
Roo,
Object Oriented Design,
Companies,
Rapid Application Development

Jeff Markham introduces Roo and SQLFire along with a demonstration of using AspectJ for SQLFire administration.

Project Voldemort: Scaling Simple Storage

Sections
Operations & Infrastructure,
Architecture & Design,
Development
Topics
QCon San Francisco 2009,
Data Access,
QCon,
Persistence,
Voldemort,
Performance & Scalability,
Conferences,
Database,
Storage,
Architecture

Jay Kreps discusses the architecture, algorithms, implementation and deployment of Voldemort, a distributed storage system. He also presents the problems solved using Voldemort at LinkedIn.

What's New and Exciting in JPA 2.0

Sections
Architecture & Design,
Development
Topics
JPA,
Java EE,
Java,
Languages,
EclipseLink,
Persistence,
Database,
TopLink,
Programming,
Hibernate,
Jfokus 2009,
ORM,
Eclipse

Java Persistence API (JPA) 2.0, introduced with Java EE 6, adds in and specifies fully many things which were missing in JPA 1.0. This presentation discusses several features of JPA 2.0 such as advanced locking, enhanced query language, a shared cache API, expression/criteria API, property standardization, more flexible object modeling and more advanced O/R mapping support.

Interviews about Persistence

Costin Leau on Spring Data, Spring Hadoop and Data Grid Patterns

Sections
Operations & Infrastructure,
Process & Practices,
Architecture & Design
Topics
Spring Data,
JavaOne2011,
Spring,
Java One,
Java,
Big Data,
Dependency Injection,
SpringSource,
Database Design,
Design Pattern,
NoSQL,
Data Access,
Clustering & Caching,
VMWare,
Languages,
Persistence,
Database,
Performance & Scalability,
Infrastructure,
Architecture,
Patterns,
Object Oriented Design,
Programming,
Design,
Companies,
Spring Hadoop

In this interview recorded at JavaOne 2011 Conference, Spring Hadoop project lead Costin Leau talks about the current state and upcoming features of Spring Data and Spring Hadoop projects. He also talks about the Caching and Data Grid architecture patterns.

Emil Eifrem on Neo4j and Graph Databases

Sections
Operations & Infrastructure,
Architecture & Design,
Development
Topics
Neo4j,
Ruby,
Neo,
Dynamic Languages,
Graph Database,
Java,
Companies,
Persistence,
Languages,
Relational Databases,
Data Access,
NoSQL,
Database Design,
Architecture,
Programming,
Database,
SpringOne 2010

Emil Eifrem explains graph databases, what domains they fit well, and the state of Neo4j. Also: how graph databases stack up against RDBMs.